def filter_s()

in source/sagemaker/sagemaker_graph_entity_resolution/dgl_entity_resolution/utils.py [0:0]

• 9 lines of code
• 5 McCabe index (conditional complexity)

def filter_s(triplets_to_filter, target_s, target_r, target_o, num_entities):
    target_s, target_r, target_o = int(target_s), int(target_r), int(target_o)
    filtered_s = []
    # Do not filter out the test triplet, since we want to predict on it
    if (target_s, target_r, target_o) in triplets_to_filter:
        triplets_to_filter.remove((target_s, target_r, target_o))
    # Do not consider a subject if it is part of a triplet to filter
    for s in range(num_entities):
        if (s, target_r, target_o) not in triplets_to_filter:
            filtered_s.append(s)
    return torch.LongTensor(filtered_s)